|
|
Absolute deviation, 绝对离差% c" G+ Y8 F* e: g. }
Absolute number, 绝对数
2 g' F1 R0 y+ TAbsolute residuals, 绝对残差6 o6 v: X! Y) Q' _5 p
Acceleration array, 加速度立体阵
; d G m M% L# M6 @+ }Acceleration in an arbitrary direction, 任意方向上的加速度0 d3 i; H' s+ ~
Acceleration normal, 法向加速度6 K2 g1 z/ w# ]/ S9 [/ y+ g( n
Acceleration space dimension, 加速度空间的维数/ S* F$ k0 B8 h; k1 P, ?+ g2 E6 m
Acceleration tangential, 切向加速度
5 d0 q* T/ r: S+ Y: BAcceleration vector, 加速度向量) o* x0 B5 F2 y' s1 q/ D
Acceptable hypothesis, 可接受假设- }, L; h- n D$ ]) ?* x9 x
Accumulation, 累积7 L# m! |8 }5 n# Y" w$ `$ C5 ~
Accuracy, 准确度" E; C3 i/ E8 W* J* ^' u7 J2 W+ b8 q
Actual frequency, 实际频数' I" c$ }0 F/ i' j
Adaptive estimator, 自适应估计量( @- P1 V- a$ E4 W" |% h3 ]0 f
Addition, 相加, j) T1 Q7 q8 B) |
Addition theorem, 加法定理# C9 ], @" M' j. N& ?1 G
Additivity, 可加性
# x: p$ w; D P5 k4 d! {/ T9 vAdjusted rate, 调整率3 _# v0 f: m5 P `3 A
Adjusted value, 校正值* d& R; d' e; g$ F$ N) L% H- C
Admissible error, 容许误差
' z; I* s! V# y& D" j) KAggregation, 聚集性
# q5 T. Z3 S* E4 LAlternative hypothesis, 备择假设
$ U/ t. g# j& W, G4 t; dAmong groups, 组间
% f9 p+ }# ]1 EAmounts, 总量" \' v! W* E8 U+ {2 N
Analysis of correlation, 相关分析0 @7 E8 T' |2 f8 G
Analysis of covariance, 协方差分析
* o. r* V5 ?+ AAnalysis of regression, 回归分析
! s# i- U8 _4 |Analysis of time series, 时间序列分析/ ~3 v2 t/ m' ?4 h; U
Analysis of variance, 方差分析
6 s' g1 ~# P7 u7 h) E* OAngular transformation, 角转换3 r' S! S: ]5 d0 ?; V6 @% F
ANOVA (analysis of variance), 方差分析8 I' a1 J0 Z5 ?1 A, ~; k5 o9 o
ANOVA Models, 方差分析模型
6 g& n: e3 s2 r1 nArcing, 弧/弧旋
& X/ H. b! ]; I6 c+ fArcsine transformation, 反正弦变换
5 {! o% f/ w7 Q" _8 CArea under the curve, 曲线面积1 F# n' Y ^4 K7 | G3 m& |
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
" Y* }# R2 X2 a; C. ~$ V& JARIMA, 季节和非季节性单变量模型的极大似然估计
* W* v' c& M+ R" }# VArithmetic grid paper, 算术格纸
0 C$ T: Y4 S9 {6 |) Y% MArithmetic mean, 算术平均数
# U3 ^! I. P y) UArrhenius relation, 艾恩尼斯关系5 W6 H Q+ x7 L
Assessing fit, 拟合的评估
k, ]1 l3 x/ M1 [Associative laws, 结合律
' u" Z @ L& i1 ?# DAsymmetric distribution, 非对称分布
# T9 K$ q1 d0 F) ?6 `/ T, iAsymptotic bias, 渐近偏倚
- q" Z6 t) M9 {0 r( WAsymptotic efficiency, 渐近效率
" \) D* d, G! R9 W9 ^8 UAsymptotic variance, 渐近方差2 y# {/ p# y9 d. [& n3 M3 G
Attributable risk, 归因危险度
( } u* F9 F: v2 h0 P$ \8 e/ OAttribute data, 属性资料
8 q- W% d+ q5 T* @. H! x) sAttribution, 属性5 v. L/ M# L3 {! a" \( {7 B
Autocorrelation, 自相关/ U6 U( d \0 f
Autocorrelation of residuals, 残差的自相关5 ~" {0 `& z! e3 S K1 |
Average, 平均数
4 }9 r7 G# u" } ~' X: k5 w, P- HAverage confidence interval length, 平均置信区间长度
5 i. `2 x. x; i% D* h+ K, ]! qAverage growth rate, 平均增长率& \8 S* \0 W/ }" o1 j* L# p
Bar chart, 条形图
. Y0 A$ I+ ?# S# \5 q6 dBar graph, 条形图, U6 f1 ]* n4 p
Base period, 基期( u @: L7 R( F. n3 y; i# \/ o
Bayes' theorem , Bayes定理
! W s, t9 A) L7 R$ QBell-shaped curve, 钟形曲线8 }1 @7 D/ A* M
Bernoulli distribution, 伯努力分布2 b2 d3 j& _: Z. A; J k
Best-trim estimator, 最好切尾估计量
6 p) e2 I. w0 V% P( \0 gBias, 偏性
& o; M1 A% s! }# A. K5 F6 H9 aBinary logistic regression, 二元逻辑斯蒂回归
# T E, c' N/ y7 R4 Q: z% N. A5 u. ^0 uBinomial distribution, 二项分布 ]8 d8 i6 g1 L: l* V
Bisquare, 双平方
: `- J4 [4 ?/ K' s: @/ C' }Bivariate Correlate, 二变量相关5 Q3 E+ t$ P$ W- W* n
Bivariate normal distribution, 双变量正态分布
: C1 O! R$ K1 C6 F& R7 EBivariate normal population, 双变量正态总体
8 v3 x4 D$ l1 `# v1 x: v. ^Biweight interval, 双权区间" m: {/ L# C. v4 ?7 Z
Biweight M-estimator, 双权M估计量. p, [( h* k; d% c) j7 l) `
Block, 区组/配伍组7 Y e4 D# S4 `& f8 c& z
BMDP(Biomedical computer programs), BMDP统计软件包
$ Z, b) h3 a9 n+ b; b: t; yBoxplots, 箱线图/箱尾图3 C' W# R* X$ B! ~9 X
Breakdown bound, 崩溃界/崩溃点( ]. B& r& q X% p
Canonical correlation, 典型相关
) J6 |, z, }+ ]- W( A$ lCaption, 纵标目
9 Q! \# |; j' o m) U$ ]Case-control study, 病例对照研究/ k* G6 r6 y. g6 Y1 s; n9 W. x
Categorical variable, 分类变量; x- W; v9 n: ~+ ]
Catenary, 悬链线
; B/ E$ O& R2 g/ `+ H9 U: \Cauchy distribution, 柯西分布
" b3 O5 |0 i7 x9 \% [4 lCause-and-effect relationship, 因果关系
0 T) z2 P2 c1 h K, OCell, 单元, }3 o4 Q) A/ A5 ?5 J
Censoring, 终检
* u+ |, U$ [6 t# DCenter of symmetry, 对称中心
, J. x! L# {. |' vCentering and scaling, 中心化和定标
( p7 x* d* c \/ m# @Central tendency, 集中趋势
' C+ z% |0 n" N2 v6 }8 UCentral value, 中心值
+ s( y( M) I& |& X8 PCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
5 R: g$ L5 I6 {! r+ x- a; e: JChance, 机遇4 T* h9 R% W4 @! a K! x2 t
Chance error, 随机误差
. ^4 w) [# _: ?0 p5 G) BChance variable, 随机变量
& ]# o( B5 v% a/ b& b3 \Characteristic equation, 特征方程
& a7 m1 n3 @; ^Characteristic root, 特征根
0 X. ^) L! w3 M* W. q- ]Characteristic vector, 特征向量
# Q* P5 J% J$ E, g3 oChebshev criterion of fit, 拟合的切比雪夫准则
9 l% {! @, J/ L9 [; qChernoff faces, 切尔诺夫脸谱图
. k1 z/ _1 h. t8 CChi-square test, 卡方检验/χ2检验. I! b) W5 T# z$ t9 X" a
Choleskey decomposition, 乔洛斯基分解6 z) J6 X" r9 C0 x% [
Circle chart, 圆图
9 E7 }5 a( D4 zClass interval, 组距2 X5 A1 ^. Z' n% S! N- ^- A
Class mid-value, 组中值
0 I7 }* {4 g& P+ ?; S5 A+ XClass upper limit, 组上限
, u4 r5 ?! ?" O3 G4 {/ Y) uClassified variable, 分类变量
: p* V c* }$ ~/ ]/ j6 ]/ mCluster analysis, 聚类分析& D. p8 B2 d8 p4 `+ h! K, Z
Cluster sampling, 整群抽样
$ w! \6 O6 Z* j, }, [Code, 代码: o z/ q$ q7 v7 P, n6 Z1 \
Coded data, 编码数据; P+ m2 B, Z' i* S
Coding, 编码
8 i T; K- z2 R, L+ T- HCoefficient of contingency, 列联系数
3 x5 k M6 q% d" f! o! m( B1 J; lCoefficient of determination, 决定系数
C" [# p* {" K8 RCoefficient of multiple correlation, 多重相关系数
d9 p4 D1 M/ N2 F7 L' NCoefficient of partial correlation, 偏相关系数
7 t \) J, Y& M- V# m9 R: t8 e$ DCoefficient of production-moment correlation, 积差相关系数
l! r0 {$ Y' K' l8 t9 a8 PCoefficient of rank correlation, 等级相关系数
7 N% ]1 r, m* {+ lCoefficient of regression, 回归系数
, h5 t. b: ]9 E2 V/ z; f# b* BCoefficient of skewness, 偏度系数# Y: u, i$ Q( T7 E: S
Coefficient of variation, 变异系数
9 G# D. t( K: A$ {9 q+ U% S7 sCohort study, 队列研究! C6 k/ f7 l6 N( x3 a# h
Column, 列
" w4 E q Z8 a# XColumn effect, 列效应
4 \( S! I- [8 t$ I! d6 uColumn factor, 列因素
% x" p2 ]; G* d1 ECombination pool, 合并/ J' k, p1 W1 A" ~- S( w
Combinative table, 组合表
+ c" S9 B% E2 k+ y# O/ B* tCommon factor, 共性因子
+ A% F: _; x" {9 \; R' LCommon regression coefficient, 公共回归系数
" | D% L/ R+ @! v+ z b uCommon value, 共同值
- S% _$ w3 T6 r: @# T$ Q! J: a+ yCommon variance, 公共方差
6 T& i( }$ x% z6 i9 U+ V; [Common variation, 公共变异0 V/ z( e; U7 P/ P$ Z
Communality variance, 共性方差$ B* W) K5 Y3 i) T4 Q
Comparability, 可比性
4 y- g" F. U8 h; NComparison of bathes, 批比较
3 [4 w3 H2 @% w; s( B- ?( oComparison value, 比较值$ w6 v7 e3 {- n" k7 h
Compartment model, 分部模型2 \' J: O3 {! I' h* W3 l
Compassion, 伸缩
5 }) G3 _8 x; ^/ I. u+ |( ?Complement of an event, 补事件
% a& e6 e1 n1 @+ u1 CComplete association, 完全正相关9 j) g8 a3 A3 s3 i1 J' P" p" v1 D
Complete dissociation, 完全不相关/ c& ^+ V1 O6 Q- K! g
Complete statistics, 完备统计量
' X+ r( S* h- X* nCompletely randomized design, 完全随机化设计/ r7 D. T2 \- I0 u
Composite event, 联合事件
/ k2 D- W5 N2 e5 p3 aComposite events, 复合事件
5 u' {3 @2 v3 q0 z% p) p: g0 kConcavity, 凹性+ O; ]$ `4 A2 `: R
Conditional expectation, 条件期望
6 ?$ p( H/ \# m1 }( C. b+ @4 G$ u+ ^9 aConditional likelihood, 条件似然
9 S$ D* M) \6 _Conditional probability, 条件概率2 U. v4 P4 u( H8 F9 y
Conditionally linear, 依条件线性' M5 l; n3 M3 U$ x- C/ y' B9 y
Confidence interval, 置信区间6 l$ d, q( |% g1 @# M
Confidence limit, 置信限) F t- c& h: H
Confidence lower limit, 置信下限0 N0 d- G% r5 R4 z
Confidence upper limit, 置信上限
0 H' _. z) Q z2 t: kConfirmatory Factor Analysis , 验证性因子分析! u3 [& y5 n8 _- ~- F- W3 E
Confirmatory research, 证实性实验研究
% @4 _5 G* ?; {: B8 ]4 G& `Confounding factor, 混杂因素0 Y1 g/ y9 R( H3 }; G
Conjoint, 联合分析% e, Q$ e8 M- f5 \1 V7 e% x
Consistency, 相合性0 o4 i0 G2 s" {
Consistency check, 一致性检验. l. q8 B- f* j
Consistent asymptotically normal estimate, 相合渐近正态估计- {" B! X/ }# Z, H4 w# ]
Consistent estimate, 相合估计) i6 o. K [. V3 ]7 r. [
Constrained nonlinear regression, 受约束非线性回归
- t5 k; u* k( j; i+ S4 rConstraint, 约束 t& q |0 i# a& n) p- [1 L' x
Contaminated distribution, 污染分布
" ^- Y2 a6 e0 rContaminated Gausssian, 污染高斯分布$ u \, Y- q4 S* ]1 _) ^
Contaminated normal distribution, 污染正态分布+ ?; g1 i2 E% _1 e; v
Contamination, 污染) L! O' m6 h: U
Contamination model, 污染模型
+ y! K2 S7 X& ?1 ~Contingency table, 列联表
4 s# o; A# n! V# A& hContour, 边界线
$ Z X" o) V+ m4 Q' G# E1 j9 DContribution rate, 贡献率8 L9 u9 T/ D( Y; g* t
Control, 对照
+ O4 x- C( a: s* @2 n! ]Controlled experiments, 对照实验" i2 z" Q. s$ ^* X( l
Conventional depth, 常规深度' j; v( D8 z9 \2 ]' z
Convolution, 卷积. d* f& A% U4 c% U9 t- Z
Corrected factor, 校正因子% X7 [% o" L" i" J8 |, U
Corrected mean, 校正均值0 K& ]- C( S( Q! s" k0 ?) H
Correction coefficient, 校正系数" F; b" U; Q, |% Q
Correctness, 正确性 g6 ^( A" I' H) T/ w N( p$ X
Correlation coefficient, 相关系数8 h9 w" f, ^& O, l8 \
Correlation index, 相关指数
( o+ d* t) q/ l- H$ H9 y, XCorrespondence, 对应+ @5 U, y S) Q6 `% }6 p
Counting, 计数3 U8 U3 W' w$ `9 c
Counts, 计数/频数
0 `7 k+ p' n% A+ a2 C+ FCovariance, 协方差& K) @5 c! v2 o7 ?* }
Covariant, 共变 3 i9 B t5 n, v, E' @: M9 _' I
Cox Regression, Cox回归% O; E+ q$ }: h1 W3 [- M
Criteria for fitting, 拟合准则6 C# |2 D, S/ b! Y# l& D; m6 _9 j
Criteria of least squares, 最小二乘准则# B! M7 c( D; C* F4 h
Critical ratio, 临界比
+ i, @1 j4 b9 t: y' E, dCritical region, 拒绝域
. {9 Q0 X- {6 H# z6 h' V8 O9 WCritical value, 临界值
0 f' p q, f, F3 {6 n) e2 xCross-over design, 交叉设计% t9 {- }% g! ?. q+ ?
Cross-section analysis, 横断面分析
" T, T' p) m* m' X! C# y" YCross-section survey, 横断面调查
( F, ^% B8 @2 G% m2 @Crosstabs , 交叉表
& W) t1 _9 ~0 j' g. uCross-tabulation table, 复合表
1 D5 [ L6 n4 BCube root, 立方根
7 B2 s( r. U( Y2 K$ Z) J8 ?Cumulative distribution function, 分布函数
9 e8 p) Z o; E$ b8 I3 r: n7 yCumulative probability, 累计概率- f& r; O7 g$ \4 R
Curvature, 曲率/弯曲
; `, {1 Q' J# w" ECurvature, 曲率7 ~3 z4 E) o6 p6 v5 A
Curve fit , 曲线拟和
g+ V% }2 l0 r& K2 X6 QCurve fitting, 曲线拟合
% {# ?' H; Z5 q$ I* O1 J' g; DCurvilinear regression, 曲线回归/ B& x1 [' b1 x* z
Curvilinear relation, 曲线关系
$ {. _9 z% P" S# `2 A* qCut-and-try method, 尝试法
% r) I, ]8 ]# _2 K B: FCycle, 周期1 A* T- S- |0 n$ U$ h
Cyclist, 周期性( Z, j$ J/ X! ]
D test, D检验* \; T' _5 a k; F
Data acquisition, 资料收集
( W/ H% O% Z1 I/ s5 L* O8 {Data bank, 数据库
' R% @* F! D0 J, e# @& bData capacity, 数据容量3 Q5 W3 x& Q" g0 Z) l7 T3 F) i8 \
Data deficiencies, 数据缺乏
+ }; g1 v; i, XData handling, 数据处理
6 c& x! S" |5 v6 C( j% W8 N' c& JData manipulation, 数据处理
5 V/ {% N. X# J" K2 tData processing, 数据处理
! N5 Z" E3 \2 UData reduction, 数据缩减' @' b% H5 }0 Y& O3 w+ \
Data set, 数据集
3 j( h, M/ g! c" ~. K. [Data sources, 数据来源: H2 K* R0 U( x4 V6 Z
Data transformation, 数据变换( [! h: w) ^) q0 F3 l; a, h
Data validity, 数据有效性 R2 m4 t6 q- s+ r* u
Data-in, 数据输入5 H) k- p. w3 W F, `4 h8 [
Data-out, 数据输出' a( B# w6 K# s1 n! W2 }3 m$ W# z/ N
Dead time, 停滞期
0 I8 T2 j8 w& l: ?# GDegree of freedom, 自由度) ?0 \$ y# _0 G7 T
Degree of precision, 精密度8 C$ _% B# V( i# g- u5 l
Degree of reliability, 可靠性程度
5 q0 A# W" W- E9 S# P2 ^1 [5 ~- b; i/ QDegression, 递减: b5 @ P- ?( O0 \/ }, R; b
Density function, 密度函数' C8 q* o+ ?; n- D3 s/ I5 c. I6 \ W+ f" q
Density of data points, 数据点的密度* Y/ ?' @9 b" z" S
Dependent variable, 应变量/依变量/因变量- ?: N) B) C( t V1 t* \* e
Dependent variable, 因变量
! A8 V) B) A1 ~5 jDepth, 深度" z" r; Y o/ H% N5 P! m1 x
Derivative matrix, 导数矩阵2 L! [; ^5 q; b$ I- N5 f
Derivative-free methods, 无导数方法4 q" L- m. e8 M% a
Design, 设计1 i# \! l. g& F* o
Determinacy, 确定性
% _% F* j9 |; Z4 dDeterminant, 行列式
1 q8 k: }& t$ UDeterminant, 决定因素5 l3 F0 b& B( j
Deviation, 离差
- Y- t- B" {( ~! x4 G3 e; s/ t6 `Deviation from average, 离均差
) g. C5 ]! E+ d! f! E' JDiagnostic plot, 诊断图) o t o9 b& Z: |' l1 ?3 y& X$ S
Dichotomous variable, 二分变量$ p) L1 L: g0 G% ?" i" o7 E, x% a4 A
Differential equation, 微分方程
+ B9 p2 u2 n ]' I6 TDirect standardization, 直接标准化法
5 ]. [5 G& q1 s2 g/ z$ x f! f6 U' iDiscrete variable, 离散型变量& `8 e% y* \3 |8 J+ Q% y( `
DISCRIMINANT, 判断 . a; Y9 h+ {5 i5 T, P0 X3 Q: a
Discriminant analysis, 判别分析
2 ?: j$ A) X# U* y; H. b2 T) VDiscriminant coefficient, 判别系数3 `; b) h) _; d' e( Q, K9 ?
Discriminant function, 判别值
4 @6 q/ _+ {2 Y- K6 W. WDispersion, 散布/分散度( @7 l$ }0 K, r9 N/ Y- U( {( W' ?
Disproportional, 不成比例的) ]6 |1 w5 w1 K* T5 y! m! ^
Disproportionate sub-class numbers, 不成比例次级组含量
5 n0 t0 x6 p. T* s: `6 CDistribution free, 分布无关性/免分布
/ Q# F% f7 `/ D) {Distribution shape, 分布形状" U4 }, j2 x5 d2 k$ Q/ W% _% h
Distribution-free method, 任意分布法
2 `+ x: o$ q$ S* @7 Z" X! g3 {Distributive laws, 分配律: J" m8 [! L4 }! c g* C* [' Y& x1 K
Disturbance, 随机扰动项
' d3 V" |$ S# Q- sDose response curve, 剂量反应曲线! g; _1 ?9 K3 V# y9 b
Double blind method, 双盲法
$ g. j P& O: `8 |8 s7 Z+ e/ }Double blind trial, 双盲试验, l9 c/ j' C: ]8 v
Double exponential distribution, 双指数分布4 \. h+ k& M) ~! H
Double logarithmic, 双对数& H+ o1 r* f+ q& f
Downward rank, 降秩+ Q( V8 z5 Q' R
Dual-space plot, 对偶空间图+ `: Z2 F+ B7 t% u% E' s6 f1 B
DUD, 无导数方法+ l$ y' |" b8 V% p
Duncan's new multiple range method, 新复极差法/Duncan新法, p! z5 c! o9 l. E$ j8 l
Effect, 实验效应
; p% u* `* d3 f$ R0 q8 wEigenvalue, 特征值6 Q: A, O1 m* G3 e
Eigenvector, 特征向量
2 w. e4 E& l" D0 u) _7 z4 fEllipse, 椭圆$ `& x9 H9 V' \+ X8 I
Empirical distribution, 经验分布; O7 v" _' E1 L, R& R
Empirical probability, 经验概率单位% R0 u* W9 b& S5 b, O! D- W
Enumeration data, 计数资料. i9 g |2 Z' l- v4 B! Y! Z2 ?# J B
Equal sun-class number, 相等次级组含量+ Z; Q& V0 f8 x9 s" c& n( p
Equally likely, 等可能+ A1 z5 \ [8 g
Equivariance, 同变性2 z8 m; S; T6 W6 k! x! {
Error, 误差/错误" S9 d. I2 y$ x0 ~1 s5 ]# u* p& r
Error of estimate, 估计误差8 f0 _5 z$ @" o- {) y
Error type I, 第一类错误
1 S# [0 c a, F- GError type II, 第二类错误
Q8 d# E( z: J& d: Q% L1 B2 B4 K8 OEstimand, 被估量
4 c, S' k$ G4 ?- s. fEstimated error mean squares, 估计误差均方% v6 d0 z* O% R7 Y/ X" z9 K/ a* |
Estimated error sum of squares, 估计误差平方和2 @* q* n# t4 _4 J: v& W. ?, I8 z M
Euclidean distance, 欧式距离4 L/ f7 v) ~5 K8 F; J; ?6 T# }
Event, 事件- |) c' j$ L @
Event, 事件# q7 i6 @1 O5 i% p6 ~
Exceptional data point, 异常数据点
# F- e8 l# i5 @+ {, DExpectation plane, 期望平面. _5 O E s4 ?+ s$ k1 ^( I' ?
Expectation surface, 期望曲面
& z! u. k/ J% w# a% gExpected values, 期望值& \( g& f% f( ?
Experiment, 实验
8 M6 l4 N4 `/ D( L: w2 p( @Experimental sampling, 试验抽样& G4 H' j" m( P) i5 \( [' x: a
Experimental unit, 试验单位
. Y& }( ]/ r5 E2 YExplanatory variable, 说明变量* h4 g$ z# X7 N w7 {) H3 r
Exploratory data analysis, 探索性数据分析) V" q1 b2 U" g! P+ \+ n
Explore Summarize, 探索-摘要
* s3 L2 W k; jExponential curve, 指数曲线) q: I/ w* b9 I, R; X- m0 q
Exponential growth, 指数式增长
( ^7 Q) K5 A% Y4 dEXSMOOTH, 指数平滑方法
- b2 s* m1 @! j$ K" D6 \, `Extended fit, 扩充拟合
/ N# e' R8 W4 n2 nExtra parameter, 附加参数3 w8 \. F( p* Y' r% ]
Extrapolation, 外推法5 V% k- i4 X6 N& y4 N+ i% V
Extreme observation, 末端观测值
5 W4 w+ {3 Y# `! C* g( \4 o8 N3 hExtremes, 极端值/极值
8 [# b2 _+ [9 }+ g9 K- B% Z% qF distribution, F分布" w" v) [9 O, X2 A6 }2 n6 _
F test, F检验
, {7 W& s, q9 d! V' nFactor, 因素/因子' ]; G8 K9 X+ a# U/ |. z6 V
Factor analysis, 因子分析
: A1 ?5 c/ j: q' G$ n3 C, IFactor Analysis, 因子分析
8 c& H( s9 G# `, |& Q1 s' xFactor score, 因子得分 " S" r8 J3 f- c
Factorial, 阶乘8 a( c: S7 c' f. b; X- A( W
Factorial design, 析因试验设计$ d: l( r1 C7 L8 d
False negative, 假阴性
2 a, q4 X& R# C2 I; s: o; wFalse negative error, 假阴性错误* z. r( c6 J4 ~2 i$ q
Family of distributions, 分布族4 k8 i7 S3 i6 u
Family of estimators, 估计量族
) V: @2 {& R; r# N+ M8 MFanning, 扇面& Q8 u7 W8 N7 A8 O8 v# x3 X) k# J
Fatality rate, 病死率
6 n& V3 |& g. x uField investigation, 现场调查3 N! O3 d7 }( O( H9 Q6 U
Field survey, 现场调查$ r5 [2 H7 O3 j l |, K+ R
Finite population, 有限总体
4 O8 _: c6 |1 E6 P* f: J( rFinite-sample, 有限样本
8 f" _5 O$ q8 q5 g. Y, HFirst derivative, 一阶导数
2 D9 s. x z1 I% ]) GFirst principal component, 第一主成分) W+ }, [+ U, D# g0 A
First quartile, 第一四分位数/ e! q2 ?7 f( ^6 r0 ]/ J: w; ^
Fisher information, 费雪信息量
, h' n Q, {* r: O0 d) aFitted value, 拟合值; e# M' O- z0 W4 V8 e3 G |: ^+ }; R
Fitting a curve, 曲线拟合
) v+ I4 n O k6 d( F- Q" @Fixed base, 定基
- G5 k& C9 _1 E; u8 f* HFluctuation, 随机起伏
8 v3 `, U! j" H+ j1 ^+ {: mForecast, 预测6 x& d# {1 f7 I
Four fold table, 四格表
8 I6 e5 i3 y, D% [, b( V- \+ y3 l5 NFourth, 四分点
6 P9 }9 r; l. a) W' B) B4 ?' TFraction blow, 左侧比率; B' G* n6 d5 o/ P% G
Fractional error, 相对误差7 u9 f7 y/ k% Y/ e% s8 g
Frequency, 频率. }4 T" w9 g# q
Frequency polygon, 频数多边图6 I U6 G/ {% C* r/ r, N
Frontier point, 界限点
4 w8 J8 r$ V+ z1 w7 IFunction relationship, 泛函关系
7 w' w4 m6 R1 c5 ~Gamma distribution, 伽玛分布
( p- _- d4 @, s3 zGauss increment, 高斯增量
; v1 Q8 k2 P/ A) w# a$ _% KGaussian distribution, 高斯分布/正态分布8 j( m2 T- i+ K$ D
Gauss-Newton increment, 高斯-牛顿增量
7 G4 b# }' m+ `: ] CGeneral census, 全面普查# h+ X; S. B: f3 G/ r1 V
GENLOG (Generalized liner models), 广义线性模型
# R8 p F }$ l' \) WGeometric mean, 几何平均数$ b, q( `' y) Q+ b+ o" V
Gini's mean difference, 基尼均差( m: e$ G e' z; P
GLM (General liner models), 一般线性模型 / F2 |3 t- D8 B; l. E
Goodness of fit, 拟和优度/配合度
' R& Y+ B v. Z# ^0 S0 z9 bGradient of determinant, 行列式的梯度
/ x7 O6 P6 i9 B8 X; g5 C3 EGraeco-Latin square, 希腊拉丁方
E) C# g d. Z7 o7 V8 ^! S* N3 q& vGrand mean, 总均值6 H( ?9 Y, m3 i1 A9 J5 R
Gross errors, 重大错误
) n) c3 w' U; J8 sGross-error sensitivity, 大错敏感度* c# v! O0 h( @2 P# E" d
Group averages, 分组平均* h, K9 n9 {/ p7 R- @. G
Grouped data, 分组资料+ w( c8 K0 N+ S s2 p
Guessed mean, 假定平均数: p! H- [" ? Y$ w5 ^$ V- W
Half-life, 半衰期8 l* t5 ?6 J; V% J, L9 e) o" i
Hampel M-estimators, 汉佩尔M估计量' C' N) M4 i3 R( z% r
Happenstance, 偶然事件
- F+ w2 y. h. C! E7 i4 mHarmonic mean, 调和均数
1 C" Y" D7 G# gHazard function, 风险均数
6 g5 c) y4 ?. NHazard rate, 风险率
# _- u9 j1 `* ]0 R8 R3 @+ FHeading, 标目 ) n) s* }5 f# i% K
Heavy-tailed distribution, 重尾分布: B. j; W+ F) a+ ?- [
Hessian array, 海森立体阵
( x. b* o8 ?& v9 D# _% |Heterogeneity, 不同质9 Q2 I2 C `9 R0 ]% K
Heterogeneity of variance, 方差不齐 . \4 E0 V: g& y5 x- ]4 A
Hierarchical classification, 组内分组
6 x% L5 c R0 U; YHierarchical clustering method, 系统聚类法
' s; {$ w- R( H. LHigh-leverage point, 高杠杆率点6 x3 Y) v) A. Y% z
HILOGLINEAR, 多维列联表的层次对数线性模型6 R/ `: C& J9 h3 ?( O$ A, p# l3 K* s) G
Hinge, 折叶点
0 `4 y6 ^) L: V8 C& w3 BHistogram, 直方图# j. L4 }! [8 W
Historical cohort study, 历史性队列研究 . G# [0 P2 L/ `# q
Holes, 空洞4 w& }1 t4 t) \9 ?! Y2 _
HOMALS, 多重响应分析
8 i. B: H: H' S6 l! MHomogeneity of variance, 方差齐性
L& f3 z2 ~( e1 wHomogeneity test, 齐性检验
; `1 c3 D# j0 p( z( q7 sHuber M-estimators, 休伯M估计量" e; H6 V. {) Y1 ]7 W$ Z( |
Hyperbola, 双曲线2 ?+ E( m/ p/ z% ]3 l7 Q: g5 @
Hypothesis testing, 假设检验
: g1 L( C+ F3 y% u, p7 x) [$ jHypothetical universe, 假设总体4 w1 a# L% u) [0 l! V3 G& _
Impossible event, 不可能事件
3 y- @' c: p& RIndependence, 独立性
Q: [0 R( I7 n6 z6 N2 \1 u+ C! Q$ R# gIndependent variable, 自变量
9 F3 q2 s2 R9 h- ~& Q& l$ sIndex, 指标/指数
3 y; l8 F) r9 {3 i$ iIndirect standardization, 间接标准化法
B; i, D8 H( @% oIndividual, 个体& {0 C) `! l5 C9 N; b7 z; Y
Inference band, 推断带( Y/ c+ B" r! I: a
Infinite population, 无限总体7 m7 k6 d# I& j& Z' ~
Infinitely great, 无穷大
) h! ~- X/ f" J- r/ D; V* b% jInfinitely small, 无穷小
* \+ t( Y' F# |& kInfluence curve, 影响曲线7 [9 j. Q. L8 A6 u5 p3 w) F
Information capacity, 信息容量. z, J/ C) y1 s- E G# Y
Initial condition, 初始条件
7 u! E* S, y+ Q+ }Initial estimate, 初始估计值: x4 Y& L& Q: c8 V
Initial level, 最初水平8 F- ^6 M* Y0 J2 s, M* q
Interaction, 交互作用0 m6 ?* w' E @7 N$ W% b2 T) g* P
Interaction terms, 交互作用项% z1 c, l# J" B8 G
Intercept, 截距4 w5 A. y7 [. ~# m6 t6 P1 `. V
Interpolation, 内插法
$ T; Q9 p8 m" K: R0 T) j# X# GInterquartile range, 四分位距/ U) K5 Q/ a, H/ q1 N4 p; ^% ^
Interval estimation, 区间估计" }! ^! o6 g( T) c6 }( v
Intervals of equal probability, 等概率区间
" U$ H1 @! X' n# y6 NIntrinsic curvature, 固有曲率5 z! i6 x; `/ @: B+ x; P1 l
Invariance, 不变性% ?' v- L5 w* u9 B2 V
Inverse matrix, 逆矩阵4 W* l4 C# g1 O& E1 [9 u
Inverse probability, 逆概率
: b& {( C$ Q9 V/ T, G! A/ NInverse sine transformation, 反正弦变换- k9 d' J; n7 f6 q) X- r0 Z2 @
Iteration, 迭代 9 E5 X6 Y" [0 M3 W* I! p1 E# h
Jacobian determinant, 雅可比行列式
# s$ a9 E6 b% A% B5 W) fJoint distribution function, 分布函数' D' o& N7 Y( v9 a% _5 H% L4 D& o0 q
Joint probability, 联合概率
, q- P) y* ^/ }4 }Joint probability distribution, 联合概率分布 ^/ m8 J) B4 N4 e7 r. B7 A! h
K means method, 逐步聚类法3 J/ ?; s p X8 {# G" a5 P
Kaplan-Meier, 评估事件的时间长度 9 O" d) \& S/ j) M1 S" E( {: s
Kaplan-Merier chart, Kaplan-Merier图
5 m4 `: s9 D/ @" V5 O Y0 oKendall's rank correlation, Kendall等级相关8 M6 V6 w* _9 `* V3 X
Kinetic, 动力学: \9 ]9 N7 z3 _. ?% d0 {* Z
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
5 s- n( L4 v6 G5 X8 h- ]+ C: ]Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验9 E7 }5 w5 A5 s
Kurtosis, 峰度; M' f7 D' \3 J x( ?
Lack of fit, 失拟2 c' @' K- \% K5 s( m( U9 Q. G4 {
Ladder of powers, 幂阶梯9 g o' z& w$ r
Lag, 滞后0 Y' b, U' y) G
Large sample, 大样本
' {! m5 E( ^0 E, y) _3 SLarge sample test, 大样本检验' ~' v: y/ Z) x+ P n/ r& Y$ ]
Latin square, 拉丁方+ ?) U( u4 P: {; N) v
Latin square design, 拉丁方设计8 m8 K0 Y. d3 v
Leakage, 泄漏& Q7 S$ s5 R, W# h
Least favorable configuration, 最不利构形3 z6 m9 X. M1 J0 Y6 ?
Least favorable distribution, 最不利分布1 F4 b$ [ }) a! m/ W! P* `. Y- I
Least significant difference, 最小显著差法+ K* A# H9 C T6 @' W! h7 _
Least square method, 最小二乘法
7 `* D) i. L1 e2 K. _2 c* mLeast-absolute-residuals estimates, 最小绝对残差估计5 B' c6 W$ ?6 D" v9 w: H5 k: N
Least-absolute-residuals fit, 最小绝对残差拟合
! }( c7 N$ K4 R) k( p& I+ pLeast-absolute-residuals line, 最小绝对残差线( t. N0 b7 ~) y$ s; S8 d
Legend, 图例5 Y! T/ {( [3 _* J7 g
L-estimator, L估计量5 j6 S+ o; l2 N! [8 i) y* l$ I9 S* k
L-estimator of location, 位置L估计量
0 Y. K. L% R: `" cL-estimator of scale, 尺度L估计量( `( s3 x" Z1 D1 t9 @! }
Level, 水平
4 h4 a5 z7 t5 `) R& U0 _Life expectance, 预期期望寿命
3 u, h( Y1 O( ?) v" Z+ y2 JLife table, 寿命表/ _. c" N; G* S* t0 O# X
Life table method, 生命表法1 L$ h1 v& {( C) N6 i
Light-tailed distribution, 轻尾分布
; c- n% R' }, X# D; kLikelihood function, 似然函数( j2 `- f) u6 |6 g% k- b# D
Likelihood ratio, 似然比- ~2 r8 p5 } x# n6 W3 F/ K3 C+ v
line graph, 线图' S/ x5 i( V# ~% R |+ g
Linear correlation, 直线相关
3 \6 P7 b8 d" n0 ^/ v" kLinear equation, 线性方程
4 V) ]3 J+ F KLinear programming, 线性规划
1 o2 H- s/ Z- F! G1 P* Y3 `5 x$ e6 BLinear regression, 直线回归7 N- n+ i& x" Q( D4 H
Linear Regression, 线性回归6 f& s- N. \, }, `& A# h
Linear trend, 线性趋势- y) J% t" P# A' E1 C
Loading, 载荷
J1 Q5 |' S. u' D% J9 [% kLocation and scale equivariance, 位置尺度同变性# v. S2 j- S* w# C
Location equivariance, 位置同变性( r- R! A( ?9 W' i( b+ T
Location invariance, 位置不变性- [, e2 U8 E, `. J2 v
Location scale family, 位置尺度族- D6 R N6 l7 k- b1 K3 T' r# V; Y
Log rank test, 时序检验
9 @6 H7 |; E% {. `Logarithmic curve, 对数曲线7 B4 u# g8 c+ `3 ?7 ?* W
Logarithmic normal distribution, 对数正态分布" F7 F* L# J* l+ l# V
Logarithmic scale, 对数尺度
5 L, y2 k' e8 x+ A1 W; a. oLogarithmic transformation, 对数变换
. R9 S% A- t' j5 }8 ~& HLogic check, 逻辑检查
' n0 x, G/ g. |9 ^Logistic distribution, 逻辑斯特分布' \5 E! u% w2 h' r
Logit transformation, Logit转换$ H; C1 j7 v* V" Q
LOGLINEAR, 多维列联表通用模型 4 ~" g7 J) P4 ^1 J) j
Lognormal distribution, 对数正态分布) B: W" r" Q' f. I1 p# x
Lost function, 损失函数
8 Z" V! K( Y: f4 ZLow correlation, 低度相关
8 j; _ d! E' K/ b2 F5 wLower limit, 下限' t/ q) p( N z F9 ]
Lowest-attained variance, 最小可达方差2 {/ L% x9 J! @. j) c
LSD, 最小显著差法的简称
$ p: G, C! K( cLurking variable, 潜在变量
& ^1 g5 @$ L' s# e2 ^+ oMain effect, 主效应6 G" X) I3 P% r
Major heading, 主辞标目6 {: W' n9 Y. ~3 V9 d! I. s
Marginal density function, 边缘密度函数
) ^' ?3 {6 S( \" e- V/ e5 D6 M% MMarginal probability, 边缘概率
' C5 v( F {7 U3 r) cMarginal probability distribution, 边缘概率分布% V; H5 O8 B, S% m6 q
Matched data, 配对资料 U9 e( c5 R9 p3 I9 o
Matched distribution, 匹配过分布% d% v: i) Z7 _; N5 v! N
Matching of distribution, 分布的匹配
- {% f6 I! Q8 aMatching of transformation, 变换的匹配" b/ h4 e! b* y( s5 C* q" j# b
Mathematical expectation, 数学期望
- \, a3 M M3 r: C, x* P( R& aMathematical model, 数学模型& x2 c+ A& j9 z7 V
Maximum L-estimator, 极大极小L 估计量3 q2 e4 ]6 b1 A
Maximum likelihood method, 最大似然法
% F; N/ ^2 c- E: z- SMean, 均数+ ]- z6 F6 h, ^8 c/ G, N
Mean squares between groups, 组间均方
; s! I2 Y1 c9 m* \; Z) Q6 cMean squares within group, 组内均方$ h* M/ Z3 J9 V: g) T. E( ~
Means (Compare means), 均值-均值比较# e: \) l, {: b5 O
Median, 中位数
' A+ g: d' f, C( D& f: O1 v9 x/ ZMedian effective dose, 半数效量
f: |$ Q, \$ w1 w- L# \Median lethal dose, 半数致死量/ H% M3 r8 v' @$ q1 P( {
Median polish, 中位数平滑
3 _* K+ t* d" ]" ?Median test, 中位数检验" K% Z+ @) Q/ F
Minimal sufficient statistic, 最小充分统计量7 S: b$ q$ ~ d J6 v& l( i( K
Minimum distance estimation, 最小距离估计0 G8 F( u$ E% d1 q# i
Minimum effective dose, 最小有效量2 E& ^8 j, K6 k# U2 k1 [5 R
Minimum lethal dose, 最小致死量* L4 l* x: q F! M# @# Z
Minimum variance estimator, 最小方差估计量
- L/ }& a$ i% Z) d HMINITAB, 统计软件包
. w* a" Y% X. oMinor heading, 宾词标目8 b) b0 A4 Z6 P2 i7 r
Missing data, 缺失值) z0 H% P0 p7 `5 |* q
Model specification, 模型的确定3 c& B: m7 r8 ^4 v( Z
Modeling Statistics , 模型统计- K6 l. H |6 _& S' Q
Models for outliers, 离群值模型" S6 S- w& F; ~ q9 h
Modifying the model, 模型的修正5 M+ H& J+ Q" x/ I
Modulus of continuity, 连续性模
) A& i! p/ h* C+ X. E% U2 D1 yMorbidity, 发病率
4 M5 Q2 Y- ]/ d$ Q; k1 aMost favorable configuration, 最有利构形
1 m" R) _9 O" b/ GMultidimensional Scaling (ASCAL), 多维尺度/多维标度
8 f" j/ e* @+ @6 ZMultinomial Logistic Regression , 多项逻辑斯蒂回归
6 K8 ]- S# x+ o0 s& N/ B. aMultiple comparison, 多重比较! F7 j. K1 N# x$ ]2 k
Multiple correlation , 复相关* R+ b, O1 g3 U& n; q% E" K C% r
Multiple covariance, 多元协方差
x; x, M+ O) H& U+ U! _Multiple linear regression, 多元线性回归/ a! Y/ @/ q% N1 O
Multiple response , 多重选项
; d- Q( J$ o9 n1 \7 @0 h2 _6 }# rMultiple solutions, 多解% c& E6 e1 g( b. Q
Multiplication theorem, 乘法定理( l- |; X( N- I, t. J0 h& y$ N
Multiresponse, 多元响应1 ?. _/ e( H! N, V- q9 r
Multi-stage sampling, 多阶段抽样
' k/ k9 Q0 ~7 J' tMultivariate T distribution, 多元T分布( h% J5 ?7 _+ i; m1 p
Mutual exclusive, 互不相容
4 h. e9 H. e5 z5 F1 R- m( dMutual independence, 互相独立+ e( ^) F9 K8 _
Natural boundary, 自然边界
w, r& {; i0 [1 {" ONatural dead, 自然死亡
0 k8 g# B6 }# B4 `$ BNatural zero, 自然零
( p+ W) [3 @! W( L/ M7 qNegative correlation, 负相关
2 o; F6 d$ s* N. |Negative linear correlation, 负线性相关
' V5 \% W5 Q6 A5 m. q6 s2 ~+ J) TNegatively skewed, 负偏& e2 Q: T h& b. \& g. \' h" A& t
Newman-Keuls method, q检验
" O, E `$ A( v. q* \) Z9 ], YNK method, q检验# i4 G |; I6 q, L8 T
No statistical significance, 无统计意义- X1 M9 E- _+ U9 \7 I4 m( g
Nominal variable, 名义变量! R4 V/ i+ u, v; G5 |! f
Nonconstancy of variability, 变异的非定常性3 _; G; ]' p$ J6 k+ l& p
Nonlinear regression, 非线性相关
5 M; E5 m" U/ y0 e3 p( E& I' L6 WNonparametric statistics, 非参数统计
# j: }; k0 L8 D VNonparametric test, 非参数检验
2 k! F5 h3 m) ^" G+ DNonparametric tests, 非参数检验
( c2 }- D/ f; J2 y5 Z Y! uNormal deviate, 正态离差0 ?- _5 o1 w$ m7 _
Normal distribution, 正态分布! S8 R- [9 ~, W) v3 C7 c* D
Normal equation, 正规方程组
. f" Q3 f7 u! ^" w* i! G/ DNormal ranges, 正常范围' O3 u! w% a* Z# t$ H
Normal value, 正常值
5 c* }7 }1 Q0 v$ r4 ?9 m4 aNuisance parameter, 多余参数/讨厌参数9 Q4 M8 t" J% k9 m9 z1 ~
Null hypothesis, 无效假设 " T$ N1 N4 ?" b& {% o' a: W
Numerical variable, 数值变量
, ]0 I" D+ I8 VObjective function, 目标函数, H" U* I$ j) E3 r2 [: q
Observation unit, 观察单位% S9 l3 [6 w8 m$ U
Observed value, 观察值9 `9 O! l2 b1 ?: A/ G
One sided test, 单侧检验
. u4 B- M6 q# M/ FOne-way analysis of variance, 单因素方差分析4 G6 K! j8 | d/ ? Z
Oneway ANOVA , 单因素方差分析
' c+ K! [1 {5 V1 s! N5 A5 G! M. FOpen sequential trial, 开放型序贯设计
+ M' Q+ f' H3 m2 W& v" d1 AOptrim, 优切尾
3 b6 x9 K O) i# m9 u) x7 YOptrim efficiency, 优切尾效率: `0 o5 }6 S. P8 ^8 J
Order statistics, 顺序统计量0 p. `0 N' V; o' w4 d1 G" ]1 U0 I
Ordered categories, 有序分类
* z5 K: h/ N" [Ordinal logistic regression , 序数逻辑斯蒂回归: f0 \. k4 S/ W: Z" t( x" O8 q4 q1 I
Ordinal variable, 有序变量
- ], [+ [$ a3 c' m2 U9 ZOrthogonal basis, 正交基* A9 v' @3 {, n0 q: M
Orthogonal design, 正交试验设计
2 U. }# p' h- ]Orthogonality conditions, 正交条件& K) Y- c1 ]/ |4 y; O
ORTHOPLAN, 正交设计
/ h% |9 x; E4 h3 Q+ SOutlier cutoffs, 离群值截断点
( k5 x9 [% o. d9 V! bOutliers, 极端值: C5 O: s) v8 o% ~, O s8 r% x
OVERALS , 多组变量的非线性正规相关 o% l8 l8 U/ b( H7 X& c+ r9 q
Overshoot, 迭代过度4 u6 z1 |- k+ _" S
Paired design, 配对设计
. B/ |4 i' U/ c. X$ J( s. U$ VPaired sample, 配对样本) }# U# ?' _3 Q# I
Pairwise slopes, 成对斜率
; r4 U* r# [4 j2 A1 M* UParabola, 抛物线$ V4 l( N e' \ i
Parallel tests, 平行试验7 {$ }$ G; x# C9 C6 A% k
Parameter, 参数
B9 w8 d& C5 G8 e8 aParametric statistics, 参数统计
0 b6 r! X8 J M/ A5 QParametric test, 参数检验
( T) }/ ? s2 n+ i; CPartial correlation, 偏相关) k! c4 J! R+ l0 Z2 g
Partial regression, 偏回归
+ p }$ a# ^9 ZPartial sorting, 偏排序( B, A4 c9 \0 F# C8 f$ Z
Partials residuals, 偏残差
- j# A& L; }( B% j; E6 ePattern, 模式
$ \- f+ D% z; X2 Y' y. H- i+ yPearson curves, 皮尔逊曲线4 y1 x4 v9 p$ O& T
Peeling, 退层" K0 R" J, u+ d; r2 P
Percent bar graph, 百分条形图
& _1 V# R; A5 C6 L0 U3 nPercentage, 百分比7 p! B4 Q' ]4 u( V/ y* O$ v" L4 o
Percentile, 百分位数1 c; ]$ F {2 ]% i5 |5 \
Percentile curves, 百分位曲线
8 I2 {* k1 }. y5 ?. ?7 bPeriodicity, 周期性, x, r' `- K/ p9 t4 w3 ?1 d9 U4 t& L; z
Permutation, 排列 d9 g& i, [& t9 W6 d
P-estimator, P估计量
9 B/ t8 Q9 Z5 T7 z; ^$ W yPie graph, 饼图
0 J( F$ Z# f6 R% F& M5 cPitman estimator, 皮特曼估计量* t( N1 }! r2 |( n7 Z+ b
Pivot, 枢轴量2 W- q' b: P. C5 L" B. ?$ u
Planar, 平坦+ n0 g) w9 X. C5 z
Planar assumption, 平面的假设: M2 l+ ?3 T0 s3 n! y5 T
PLANCARDS, 生成试验的计划卡# A- C' ], S8 A' h
Point estimation, 点估计. U9 T4 C E% P
Poisson distribution, 泊松分布
, K# ]# j+ [/ H3 U: F( FPolishing, 平滑" \& d: H2 r3 z
Polled standard deviation, 合并标准差1 `, V6 y; `0 t5 x, D5 j
Polled variance, 合并方差
0 H8 h4 v3 `1 C5 V6 Y% {Polygon, 多边图
( u0 }2 T2 e( O6 T+ L/ ~Polynomial, 多项式2 x, ?4 r# ?) c, R8 c
Polynomial curve, 多项式曲线) i9 l1 c! ~8 T2 I5 L' k+ S
Population, 总体
- ]/ \- l! p) APopulation attributable risk, 人群归因危险度* b7 I7 E4 H* y- |: A/ b
Positive correlation, 正相关: _- a6 t' K* z) z
Positively skewed, 正偏
. G8 a u0 @ z" ?1 \3 WPosterior distribution, 后验分布
7 m/ ^' Z0 q8 y. I" l2 v4 M; V7 [; P. ?Power of a test, 检验效能6 E# M8 x* _; H
Precision, 精密度
. ^4 J% }- d3 }3 m& w3 b$ A7 x2 dPredicted value, 预测值
' a% p4 S2 O2 u T9 `3 y+ V' o1 pPreliminary analysis, 预备性分析
( l2 s, [$ [. Q! v$ N% d$ bPrincipal component analysis, 主成分分析0 e# \' T0 B& X7 ~! e5 R4 F
Prior distribution, 先验分布0 |0 @( x# `0 l. j3 A: d) Q( a' f4 i
Prior probability, 先验概率
. z5 Y5 ~. O; |5 h' o2 E, zProbabilistic model, 概率模型
! l: b" z- s( i( S+ b( V Jprobability, 概率
, W# K/ q1 l! O8 M1 WProbability density, 概率密度+ ?/ f( J1 @+ ?$ n/ ~
Product moment, 乘积矩/协方差
9 z. G1 g) Y' D6 o! VProfile trace, 截面迹图
% c# I3 l. |0 GProportion, 比/构成比
" R4 M2 j6 }/ ?( ZProportion allocation in stratified random sampling, 按比例分层随机抽样
, f/ P4 H" E1 s' ^& zProportionate, 成比例
+ T' C7 T+ p% z# d& L: gProportionate sub-class numbers, 成比例次级组含量; X9 n" I* I- a" C5 ?' R& M; ]
Prospective study, 前瞻性调查
, n* v; k: b2 j+ l) E) N+ y3 dProximities, 亲近性 2 Y# q8 b* s8 n% g0 c
Pseudo F test, 近似F检验2 L( s0 E! D3 v" m/ N; A
Pseudo model, 近似模型
, U5 `5 X; R* ~+ uPseudosigma, 伪标准差0 C" K: }7 u. ?
Purposive sampling, 有目的抽样% U$ |/ z4 i, Q8 f' H
QR decomposition, QR分解4 O C' O& i( ]
Quadratic approximation, 二次近似5 x3 p; p& \ J5 {9 v1 j2 k, V
Qualitative classification, 属性分类3 G* X) P: `+ R3 Q2 r, {
Qualitative method, 定性方法% Q& [+ V s% T* s0 R) m: H
Quantile-quantile plot, 分位数-分位数图/Q-Q图
+ D" x' R$ m. l8 TQuantitative analysis, 定量分析
: s- `$ \) `. I* z( P3 x0 {2 M7 j; CQuartile, 四分位数# N6 G, E8 e7 B2 a% Z
Quick Cluster, 快速聚类$ ]0 c7 |/ |, T' y, s6 k4 P( H6 ^
Radix sort, 基数排序
' S3 ~+ ? T5 A9 oRandom allocation, 随机化分组
- J3 [! q# e7 D# u: _! SRandom blocks design, 随机区组设计
7 Y6 K V/ C" J/ URandom event, 随机事件
' |0 O9 l" x j u. u2 _Randomization, 随机化# ?' h( C; R- c; O4 Z% v
Range, 极差/全距: Z4 q J' g5 a. I6 o3 I
Rank correlation, 等级相关
5 z5 O4 w) R3 SRank sum test, 秩和检验
) g6 i$ A* p% VRank test, 秩检验 h( D. m3 J. j0 ^8 v& }
Ranked data, 等级资料; V5 L. v, N0 B
Rate, 比率
/ ?1 ]% f' h8 E. P9 C( kRatio, 比例" ]! \/ b' W1 m# |, J" Z
Raw data, 原始资料# M/ j- E( A1 L/ ]3 v* w e! W
Raw residual, 原始残差3 b' H/ E9 q; K
Rayleigh's test, 雷氏检验! K$ d# C/ h4 A% _2 L* y/ i$ s! a
Rayleigh's Z, 雷氏Z值 7 i% z- e) x4 @4 [0 s* c3 I
Reciprocal, 倒数, d1 ?( l: [& A, }6 }
Reciprocal transformation, 倒数变换
( j; j2 H9 C* u5 K* F$ kRecording, 记录
& F2 A$ F0 B- H4 A2 M2 C5 LRedescending estimators, 回降估计量) K, N Y6 L* Q& ]
Reducing dimensions, 降维
. W/ _, O( e. Y6 s" [Re-expression, 重新表达
1 ]# x7 n) k% {( q- J# y) `. JReference set, 标准组
: m! F4 o( ]* |) Z# H4 @Region of acceptance, 接受域
- `0 q# F4 H/ o' @- LRegression coefficient, 回归系数( d* e/ k+ P S
Regression sum of square, 回归平方和& A" z3 ?- ?7 z/ v R, }+ w
Rejection point, 拒绝点# f' A% T. A4 T( Y; d. S4 @
Relative dispersion, 相对离散度/ L0 @% X& ]" O6 Y
Relative number, 相对数: z1 c0 ^( @$ U4 f, F' Z
Reliability, 可靠性; b; A7 ^7 X$ E/ y. Z
Reparametrization, 重新设置参数
$ R3 h; j, z. d5 k+ v) h3 EReplication, 重复
9 m8 q- ]. ^- j( ]8 [7 u. rReport Summaries, 报告摘要
" L9 c. [6 {+ U- KResidual sum of square, 剩余平方和2 _. r6 S7 R0 g
Resistance, 耐抗性) v: @7 N3 o; _0 k# }. y8 |
Resistant line, 耐抗线
! I) ?# c" ]" k/ c A, f+ M$ ?Resistant technique, 耐抗技术
! [, O5 ^9 Q6 f8 q X4 CR-estimator of location, 位置R估计量
, ^' D' f5 y0 R! y% u2 @+ XR-estimator of scale, 尺度R估计量" m% n3 k+ q% I; A9 L
Retrospective study, 回顾性调查$ r1 I% d4 d1 m" O9 c; e. |
Ridge trace, 岭迹
0 `2 A8 Z' [+ W2 s; O0 ~Ridit analysis, Ridit分析9 s6 u1 Z' w) P5 Y
Rotation, 旋转
1 W( @' M* p- r. nRounding, 舍入' {: J4 T& U3 j; R0 s
Row, 行
( t4 U$ b+ }& `/ }# DRow effects, 行效应
H& @ R) N! H/ X; dRow factor, 行因素: m9 h' H5 O1 ?8 A! h% J
RXC table, RXC表
$ O& k. e( m l1 R& q& dSample, 样本
' f3 K [6 ~" o2 JSample regression coefficient, 样本回归系数
) ]& \! p3 c9 J2 K# M" T, k( zSample size, 样本量2 n) q5 D8 M0 N" o
Sample standard deviation, 样本标准差. R$ u O+ R/ M8 c# q9 B
Sampling error, 抽样误差2 c Z- J9 A1 E1 X
SAS(Statistical analysis system ), SAS统计软件包
' b+ E& ]1 n$ _" l t1 U) b; E* d0 FScale, 尺度/量表
5 s F, O2 Q, Q( F) } kScatter diagram, 散点图
" Q. {) [2 \( f1 b: x9 jSchematic plot, 示意图/简图
6 U5 y6 j8 x! L$ q" c, z! k( FScore test, 计分检验* \3 y" P% e, T, I1 F% _0 f
Screening, 筛检
+ L7 {! g5 O4 E3 P& W# fSEASON, 季节分析
! s$ d: Z/ x/ Z$ c8 S; N6 b, wSecond derivative, 二阶导数
, s K% a/ r$ n& nSecond principal component, 第二主成分! H$ h4 E' C- Q/ Q! P: E, a
SEM (Structural equation modeling), 结构化方程模型 - Y e' m0 L8 N, H4 E5 H* |
Semi-logarithmic graph, 半对数图' t1 M! A4 z$ i9 C$ x1 H& z
Semi-logarithmic paper, 半对数格纸- v* R, y$ z$ A! G8 e0 J
Sensitivity curve, 敏感度曲线
; l4 a# ?; _3 u& m$ WSequential analysis, 贯序分析
4 Q( U c q9 O6 B) oSequential data set, 顺序数据集0 [! G* e' l' N% @) I% W
Sequential design, 贯序设计5 e- s5 D- ?5 ^5 P& u
Sequential method, 贯序法% V2 M# X5 s4 B- |) t. y+ s# H
Sequential test, 贯序检验法% w/ c$ E0 _ @# b
Serial tests, 系列试验/ c3 n) i1 G& S! j6 r2 D) {0 \
Short-cut method, 简捷法 9 \/ P5 |4 Q* F
Sigmoid curve, S形曲线' o% u# |- [# y& T: P) f
Sign function, 正负号函数
- i$ |) p: C7 _( `- OSign test, 符号检验
1 W. m3 ^) L9 ?3 p- ~; D2 TSigned rank, 符号秩/ [" Y9 C7 L9 t f/ H/ A) x
Significance test, 显著性检验' L; E! x, L y8 S
Significant figure, 有效数字4 o' r" M. A$ |) H
Simple cluster sampling, 简单整群抽样6 m/ O- V$ h8 L( S& T" ?: i4 p, W
Simple correlation, 简单相关
e1 A" u# ^: r: y. wSimple random sampling, 简单随机抽样
9 |& R" B+ b5 `3 y* @& nSimple regression, 简单回归
4 s8 w! k% i8 I/ Csimple table, 简单表
: B- d. _+ V6 n, D& SSine estimator, 正弦估计量3 b4 y0 u! _4 ^/ |9 z
Single-valued estimate, 单值估计
% o! I1 R8 X) J6 ASingular matrix, 奇异矩阵
: {$ f$ u: C2 A* e3 i4 I1 R$ P! }( gSkewed distribution, 偏斜分布. h/ Q8 {5 Y' y5 v$ q7 F1 h
Skewness, 偏度4 [) C4 w7 R6 P7 e' g& n' h) E; K
Slash distribution, 斜线分布
) d. x7 J/ ]7 S! kSlope, 斜率, J+ N1 |% e3 J/ Y4 u& D
Smirnov test, 斯米尔诺夫检验
# B- l/ u& B" ?4 T) d( qSource of variation, 变异来源9 }- Z. \3 b! t% \ q- v( s' P
Spearman rank correlation, 斯皮尔曼等级相关. j! w7 h1 T8 t
Specific factor, 特殊因子9 o$ H9 \$ r' U3 o- i/ e; v
Specific factor variance, 特殊因子方差
- ]; q9 ?7 @3 \4 aSpectra , 频谱
$ C; X `) [8 ]0 x& R4 D8 g0 tSpherical distribution, 球型正态分布
o; `' G+ g$ V% T0 N1 j4 ~& cSpread, 展布% r* G1 m& z7 f1 c( m6 V
SPSS(Statistical package for the social science), SPSS统计软件包# ~; m& V0 J7 D8 |& e. O
Spurious correlation, 假性相关0 d& z5 |8 h6 x7 j7 S8 _1 t) @
Square root transformation, 平方根变换. b4 |- k* ~- i8 m; o4 C* g; X
Stabilizing variance, 稳定方差
( X/ {! T1 V, T c, oStandard deviation, 标准差
6 g0 C0 g2 L( c2 MStandard error, 标准误
9 {# v& n) O5 O1 p/ x- CStandard error of difference, 差别的标准误
M7 q# |$ ^$ i0 CStandard error of estimate, 标准估计误差) D$ L* R$ K4 M% E3 U1 }# l
Standard error of rate, 率的标准误
2 ~/ T4 u" W* v3 q- s6 B" V2 tStandard normal distribution, 标准正态分布4 E5 i5 ~" {( K2 J
Standardization, 标准化
; C) P# j1 B6 r( ^2 z2 ~$ j2 J* SStarting value, 起始值
/ B, S, G; \, N9 Z UStatistic, 统计量" G+ G0 u6 c- d4 _- O+ N. W/ v8 A9 B
Statistical control, 统计控制& N) R) X) e( C
Statistical graph, 统计图9 k8 S& ~, r( @6 u- ]
Statistical inference, 统计推断4 x; q V+ T9 q) a, `2 U
Statistical table, 统计表
6 T; W! t2 x3 p) P0 a7 zSteepest descent, 最速下降法6 n& r9 [0 p; h4 q' Y& h
Stem and leaf display, 茎叶图
1 p6 i$ y6 A8 h3 A1 q+ {* hStep factor, 步长因子
\+ w* R8 l+ z* |; q- WStepwise regression, 逐步回归
+ B. K& n" J0 k9 Q6 l6 D3 o3 BStorage, 存
8 ]% A' J, J% T6 n0 a- v0 N1 aStrata, 层(复数)
% {: ?. u- N& K0 J d# nStratified sampling, 分层抽样
/ [, C: R( h. j; R# x2 K& RStratified sampling, 分层抽样
2 B8 K6 }) p j) S7 O! bStrength, 强度8 J8 D( m. k3 i* Q" e
Stringency, 严密性
/ g. g+ |' ?* f6 ?. `/ |% @Structural relationship, 结构关系
: `/ T) A8 @4 |% _Studentized residual, 学生化残差/t化残差1 d2 _) R; R9 y$ x4 Q5 h2 _
Sub-class numbers, 次级组含量
- l% i3 N$ V& N; J3 s9 @+ bSubdividing, 分割) {# ~& K- E8 U g: o, Q/ Q
Sufficient statistic, 充分统计量0 I! R2 U2 U) K4 @
Sum of products, 积和. ~1 P7 e1 W; E* c1 s- r
Sum of squares, 离差平方和$ R2 `6 [/ c$ T8 c9 \) u
Sum of squares about regression, 回归平方和2 H4 D% c ~8 H6 h' b
Sum of squares between groups, 组间平方和
4 S/ j: P1 I6 nSum of squares of partial regression, 偏回归平方和. o, _2 O; x0 F0 _2 K
Sure event, 必然事件
) v6 {5 f& C' b& b( K4 V4 VSurvey, 调查, F6 e3 P( E) m- k- j5 n% N
Survival, 生存分析0 E0 ~$ L: f0 u2 g
Survival rate, 生存率
2 x8 u( ?7 C/ J4 ~Suspended root gram, 悬吊根图" l& [1 b/ s, Q+ n, I0 ~
Symmetry, 对称3 v& F) Z, J( U( o
Systematic error, 系统误差
5 ~3 u& Y% J+ I0 t* b8 e9 aSystematic sampling, 系统抽样4 S7 u5 e/ O L2 v0 F) a
Tags, 标签' ~7 w" j- k8 B; ^
Tail area, 尾部面积
& Q% X8 |& d7 z: A& tTail length, 尾长
. L7 l: Z7 O; u b6 H7 VTail weight, 尾重
! O3 b9 H( B( v$ DTangent line, 切线
( m3 _9 X v) S4 g3 \ I# J( M0 eTarget distribution, 目标分布2 k" u" Y4 u6 N6 S3 P1 S/ r
Taylor series, 泰勒级数# p: m) _. {4 @* _9 C
Tendency of dispersion, 离散趋势
6 W, v! W/ V: v; w. a& V' Y& sTesting of hypotheses, 假设检验5 m4 g& }, I0 s
Theoretical frequency, 理论频数# t% G# ^/ b7 v5 C |4 o
Time series, 时间序列7 X! }" n/ a3 I9 C! V9 K
Tolerance interval, 容忍区间) Z8 \8 ^4 t- U2 K
Tolerance lower limit, 容忍下限
) }8 j |8 t' h# J" k3 _Tolerance upper limit, 容忍上限
: n' j; o$ [% k; c! ?9 F' _6 @Torsion, 扰率
9 |0 R( E4 [$ x) E3 ]7 m& @( wTotal sum of square, 总平方和
$ Y$ D3 l' `) G8 R3 [ f3 YTotal variation, 总变异
, t) z6 A# s4 {8 L& R; ?Transformation, 转换
8 T' n( o! P- j4 MTreatment, 处理
1 ~2 s+ E. j1 F! A7 i; ?Trend, 趋势/ ]8 J: ?* n" ~* O, c% I
Trend of percentage, 百分比趋势' k2 M5 w2 @+ L3 n) U9 k% X
Trial, 试验
, g0 M& n/ x* n aTrial and error method, 试错法
8 J; F7 E/ |# Q/ n3 K: A4 ]* bTuning constant, 细调常数
- P8 a ^9 E; k- j; M7 X& PTwo sided test, 双向检验
7 @3 u& U+ p5 w, F, CTwo-stage least squares, 二阶最小平方
. W( `; x7 x" P# l# ~, [Two-stage sampling, 二阶段抽样& K) q! _0 v2 }, d k- l b+ a* i% u( C
Two-tailed test, 双侧检验6 R. U, A: J7 b2 w4 r
Two-way analysis of variance, 双因素方差分析
( B2 ~% l {3 A3 \5 KTwo-way table, 双向表4 W: Y1 }& H& o$ Y" ?
Type I error, 一类错误/α错误1 z+ O& M+ J @! x) `/ b
Type II error, 二类错误/β错误7 P/ }& q+ |8 r# W/ \) L* a% R' E
UMVU, 方差一致最小无偏估计简称# @* _( o5 ]9 w1 C" Q$ K0 y
Unbiased estimate, 无偏估计2 y& m$ F$ F; M' P: K3 j6 j% G
Unconstrained nonlinear regression , 无约束非线性回归
" a- x J4 Z! O$ I5 z1 h6 vUnequal subclass number, 不等次级组含量" a7 k/ Q# Y @7 {* K- O* C
Ungrouped data, 不分组资料
2 L* P# M0 A3 J9 d @0 `Uniform coordinate, 均匀坐标1 m9 v- y' M! d8 m7 ^( x- x" {- I
Uniform distribution, 均匀分布( }8 {% n1 ?" I
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计( O( p/ P- Z; C. u( @
Unit, 单元' O3 Y! Y% D1 k$ Q; ~
Unordered categories, 无序分类0 g3 P" z) X/ N
Upper limit, 上限
- C s! ^; t* \( r& E8 e0 \Upward rank, 升秩2 E3 S8 {; H* S% e( o
Vague concept, 模糊概念
; s% }7 l7 E! z+ @Validity, 有效性
* S9 h B0 J' V# F1 t. ^) G& }VARCOMP (Variance component estimation), 方差元素估计
. B; b+ T& h+ S3 L" \Variability, 变异性% M I; @7 E& L: t8 j8 ` j1 b( G
Variable, 变量6 `( M! a0 k4 u7 C4 E
Variance, 方差
) Z. z/ e' J6 b' ~Variation, 变异
5 X0 }2 D% P o- f" H. aVarimax orthogonal rotation, 方差最大正交旋转, @4 k' [7 v+ A3 ?
Volume of distribution, 容积 T; z( O+ R x9 ~1 ? x# \
W test, W检验
: s: [; H# i# m$ VWeibull distribution, 威布尔分布( j2 Y) @% I/ s: l6 f
Weight, 权数
/ _9 J1 j* d t) t; Q5 yWeighted Chi-square test, 加权卡方检验/Cochran检验* g- T' }0 @0 t9 K# u8 v
Weighted linear regression method, 加权直线回归
" J5 e: @* o) v& d$ v) y I9 d6 J# iWeighted mean, 加权平均数
- B" p9 B( n1 p, t$ JWeighted mean square, 加权平均方差9 e3 ]( S2 F! _5 ^1 _: u' l; ]
Weighted sum of square, 加权平方和8 K0 |2 M# I8 S: l5 [
Weighting coefficient, 权重系数$ J' U" Q( `; h8 u! E
Weighting method, 加权法
( u$ ?2 x9 \% ]4 TW-estimation, W估计量0 S! j( Q9 Q L) I
W-estimation of location, 位置W估计量
3 s3 p$ @4 e! Q8 s$ H8 BWidth, 宽度
3 e6 a* F2 g6 {' j/ T; q& f+ eWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
% s/ t5 C7 e' k% x! j5 d. bWild point, 野点/狂点' F c* c' `( u) p; T4 G
Wild value, 野值/狂值! ~$ A6 A7 [. p
Winsorized mean, 缩尾均值7 _$ J& d: h( F# B. F
Withdraw, 失访 ( U- ^; ~* W8 J: s! C) f3 I& \
Youden's index, 尤登指数
$ B. k; c2 ?' h3 R# m- WZ test, Z检验
+ A4 K; ]6 v7 t% }4 m' VZero correlation, 零相关
, ~, |% x8 p2 lZ-transformation, Z变换 |
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